Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation
tarafından
 
Sanchez, Daniela. author.

Başlık
Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation

Yazar
Sanchez, Daniela. author.

ISBN
9783319288628

Yazar
Sanchez, Daniela. author.

Edisyon
1st ed. 2016.

Fiziksel Niteleme
VIII, 101 p. 57 illus., 50 illus. in color. online resource.

Seri
SpringerBriefs in Applied Sciences and Technology,

İçindekiler
Introduction -- Background and Theory -- Proposed Method -- Application to Human Recognition -- Experimental Results -- Conclusions.

Özet
In this book, a new method for hybrid intelligent systems is proposed. The proposed method is based on a granular computing approach applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) with a Granular Computing (GrC) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical genetic algorithms (HGAs) are techniques used in this research work to improve results. These techniques are chosen because in other works have demonstrated to be a good option, and in the case of MNNs and HGAs, these techniques allow to improve the results obtained than with their conventional versions; respectively artificial neural networks and genetic algorithms.

Konu Başlığı
Engineering.
 
Artificial intelligence.
 
Neural networks (Computer science).
 
Computational intelligence.
 
Artificial Intelligence (incl. Robotics).
 
Mathematical Models of Cognitive Processes and Neural Networks.

Yazar Ek Girişi
Melin, Patricia.

Ek Kurum Yazar
SpringerLink (Online service)

Elektronik Erişim
http://dx.doi.org/10.1007/978-3-319-28862-8


Materyal TürüBarkodYer NumarasıDurumu/İade Tarihi
Electronic Book17296-1001Q342Springer E-Book Collection